This paper aims to implement a fail-safe function based on the MOD (Moving Object Detection) algorithm on an embedded board. When the input image quality of the camera deteriorates due to a change in the driving environment, it is necessary to automatically detect the input image quality and provide a warning that the MOD function cannot be operated normally. When the vehicle equipped with a camera without the auto expose function drives in a dark area, the threshold value is determined by analyzing the brightness value of the input image, and a Laplacian filter based method is used to evaluate the occurrence of fail due to image distortion in the rain. In addition, we propose a weight reduction method for implementing the Moving Object Detection (MOD) algorithm executed in a PC environment as an embedded environment. The performance of the proposed fail-safe method was evaluated using the confusion matrix. The obtained precision and recall rates were 94.79% and 95.35%, respectively. The MOD algorithm compares the GT (Ground Truth) recorded in 15,216 images obtained in an actual vehicle driving environment and the performance realized in the PC environment by building the stored image database and carrying out the performance evaluation. In the embedded environment, the performance is realized at an average speed of 15 FPS or greater. This proved the applicability of the proposed method for realistic car operation.

A smartwatch is a wearable computer equipped with sensors. It can be used to provide fitness- or healthcare-related functionalities. This article presents three versions of a smartwatch application for prompting a user to stretch during the user's daily life. The first version just reminds periodically the user that it is time to stretch and then guides the stretching motion. In contrast, the second version evaluates how correctly the stretching motion is made and provides success/fail feedback for the user. The third version adds gamification elements to the second version. With these three versions, an elaborate user study was performed with 42 participants. The results show that the reminders were effective in relaxing the mental/muscular tension of the users and the motion evaluation feedback encouraged the users to stretch more. In contrast, the effectiveness of gamification was not proven. This is the first study to prompt stretching exercise and evaluate it with a smartwatch. It can help develop effective healthcare applications on wearable devices.

The PLDWS (Parking Line Departure Warning System) is one of the important ADAS (Advanced Driving Assistance System) functions when a driver recognizes the parking situations. We proposed the new real-time PLDWS algorithm and its real-time implementation based on the NVIDIA Jetson TX2, which is an embedded board environment. We showed the processing speed that is applicable to actual production vehicle and the same performance result as PC environment. A wide-angle camera is mounted on the front, rear, left and right sides of the vehicle, AVM (Around View Monitoring) images are obtained by synthesizing one Top-View image using four camera input images that have been calibrated. Considering that the visible range of the AVM system varies depending on the mounting position of the vehicle, the actual distance of the AVM image is measured and designated as ROI (Region of Interest) to the front and rear, right and left 2 meters from the vehicle. The whole ROI was partitioned into 3×3 grid regions, and the algorithm determined whether the parking line is crossed for each partitioned region by trained deep learning classifier, and finally a warning signal generated for the system. We also discussed the issue of porting to NVIDIA Jetson TX2 board to enable implementation of the parking line departure warning system into the vehicle.

MOD (Moving Object Detection) development methods were used motion region detection methods in image, but it is necessary to detect the position and the size of obstacles in a warning area for collision avoidance in a low speed vehicle. Therefore, this paper proposed the new obstacle detection algorithm. First, the proposed algorithm detects the motion region using MHI (Motion History Image) algorithm, which is based on motion information between image frames. After the algorithm is processed by a high-speed and real-time image processing of a moving obstacle, a warning logic system receives the information of the position and the size of the obstacle nearest to a car. Finally, it determines warning signal send to the control part or not. The proposed algorithm recognizes both fixed and moving obstacles such as cars and buildings using 4 - channel AVM camera images and has a fast calculation speed. After we simulated with the image DBs and the simulation tool, we have 80.07% with the average detection rate.

It has been claimed that wearable devices are useful for healthcare applications by providing functionalities such as idle alerts, pedometer, heart-rate measurement, and calorie calculation. However, these functionalities have the limitations of providing only passive assistance. In order to prompt users to do physical activities, we developed a prototype application for active assistance, which works on smartwatch devices. It guides users to stretch their arms periodically during their daily lives. For effective guidance, we integrated motion recognition and gamification elements. We performed a user study to confirm the usefulness of our approach.

Recently various cognitive radio network models are suggested and analyzed. In particular, cooperative cognitive radio network model considers cooperative relaying of secondary users in cognitive radio networks, which utilize the spectrum occupancy efficiently. However, such cooperation may not occur when secondary users have a better alternative, spectrum leasing. Therefore, in this paper, we study the impact of leasing in a network model with game-theoretic analysis. We first show the importance of the problem with a simple two-secondary-user game. Finally we extend our formulation and analysis to explicitly incorporate the effects of lease strength for a n-secondary-user game given the occupancy model of primary users.

Security is one of the important P2P storage cloud issues. RCM (the Resource Chain Model) is a trust model for the security. One problem of RCM for P2P storage cloud to be considered is which the best path is for each neighbor. Usually, for each neighbor, it is possible to get more than one resource path and such resource paths can be good candidates for use. The most widely used and easiest tree is the binary tree, and thus it is appropriate to employ binary trees in RCM.

This letter analyzes a resource chain trust model for P2P reputation-based systems. Many researchers have given a lot of efforts to reputation-based system area and some of them have made good theoretical models. Problems are to spread malicious contents whereas the remark that such models only concentrate on the relationship between the node and its direct neighbors is still controversial. To solve the problems, we introduced the RCM (Resource Chain Model) and the Enhanced RCM. In this letter, we analyze the models and then show usage of our models can help us to find the best and safest location efficiently and decrease the number of malicious transaction.

SUMMARY This letter analyzes a resource chain trust model for P2Preputation-based systems. Many researchers have given a lot of efforts toreputation-basedsystemareaandsomeofthemhavemadegoodtheoreticalmodels. Problemsaretospreadmaliciouscontentswhereastheremarkthatsuch models only concentrate on the relationship between the node and itsdirectneighborsisstillcontroversial. Tosolvetheproblems,weintroducedthe RCM (Resource Chain Model) and the Enhanced RCM. In this letter,we analyze the models and then show usage of our models can help usto find the best and safest location efficiently and decrease the number ofmalicious transaction. key words: P2P trust model, reputation, P2P networks, credibility, chainmodel 1. Introduction P2P reputation-based trust model is being one of the mostchallengingresearchtopicsofP2Pworld. TherearenofixedserversandclientsinP2Psystems. Allnodesinthenetworkcanbebothclientsandserverswithad-hocconnections. Ex-amples are SepRep, TACS, and RCCtrust[1]–[3]. PeerTrustisadynamicP2Pmodel[8]. ThegeneralmetricofPeerTrustis:

In RFID security(Gildas), few mechanisms focus on data protection of the tags, message interception over the air channel, and eavesdropping within the interrogation zone of the RFID reader(Sarma et al.a)(Weis et al.). Among these issues, we will discuss two aspects on the risks posed to the passive party by RFID , which have so far been dominated by the topics of data protection associated with data privacy and identity authentication between tag and reader. Firstly, the data privacy problem states that storing person-specific data in an RFID system can threaten the privacy of the passive party. This party might be, for example, a customer or an employee of the operator. The passive party uses tags or items that have been identified as tags, but the party has no control over the data stored on the tags. Secondly, the authentication will be carried out when the identity of a person or a program is checked. Then, on that basis, authorization takes place, i.e. rights, such as the right of access to data are granted. In the case of RFID systems, it is particularly important for tags to be authenticated by the reader and vice-versa. In addition, readers must authenticate themselves to the backend, however in this case there are no RFID-specific security problems. There have been some approaches focusing on the RFID privacy and authentication issues, including killing tags at the checkout, renaming the identifier of the tag, physical tag password, hash encryption, random access hash and hash based ID variation. The last three approaches of these will be discussed in detail in this chapter. We will not discuss the remaining approaches in this chapter as they are physical solving approaches. The last three approaches are security protocols(Ryan & Schneider) that play the essential role of minimizing the burden of privacy and authentication problems. As with any protocol, the security protocol comprises a prescribed sequence of interactions between entities, and is designed to achieve a certain end. Security protocols are, in fact, excellent candidates for rigorous analysis techniques: they are critical components of distributed security architecture, very easy to express, however, extremely difficult to evaluate by hand. Formal methods play a very critical role in examining whether a security protocol is ambiguous, incorrect, inconsistent or incomplete. Hence, the importance of applying formal methods, particularly for safety critical systems, cannot be overemphasized. There are two main approaches in formal methods, logic based methodology (Gong et al.), and tool based methodology (Hoare)(Lowe)(FDR). In this chapter, we specify hash based RFID security protocols(Sarma et al.a) as the previous work that employs hash functions to secure the RFID 6

In wireless communications research, a number of literature assume that every node knows all of its neighbor nodes. To this end, neighbor discovery research has been conducted, but it still has room for improvement in terms of discovery delay. Furthermore, prior work has overlooked energy efficiency, which is considered as the critical factor in wireless devices or appliances. For better performance with respect to the discovery delay and energy efficiency, we proposed a novel p-persistent-based neighbor discovery protocol and devised a simple and light algorithm estimating the number of neighbor nodes to support the proposed protocol. Our protocol requires a lower delay and a smaller number of messages for the discovery process than the existing protocols. For extensive performance evaluation, we adopted extra comparison targets from other research areas within the same context. Copyright © 2011 John Wiley & Sons, Ltd.

(D.Sc.) -- Towson University, 2008. Thesis approval page signed by thesis committee members and the Dean of the College of Graduate Studies and Research included in print copy of thesis.

A malicious peer's behavior is one of the most challenging research areas of the P2P world. Our previous reputation-based trust model approach, which is based on the resource chain model (RCM), prevents malicious peers from spreading malicious contents among the open community. Moreover, a study on the malicious behavior over P2P community leads us to recognize a malicious node. The purpose of this paper is to identify malicious nodes based on the new resource chain model. In addition, the research includes the analysis of behavior of malicious peers on P2P networks. The study on various malicious behavior strengthens the existing resource chain model and allows us to keep P2P network much more reliable and stable.

In traditional symmetric watermarking schemes, the key used for watermark embedding must be available at the watermark detector. This leads to a security problem if the detectors are implemented in consumer devices that are spread all over the world. So asymmetric watermarking schemes, also named public key digital watermarking schemes attract more and more attentions. In such a public key watermarking system, the private key is used for watermarking embedding and the public key is used only for watermarking detection. The private key is kept for secret, and the watermarks cannot easily be removed with public key. Several latest proposed public key watermarking schemes are reviewed in the paper, and their performances are analyzed.

Great attention has recently been shown to computer security. Therefore, many mechanisms have been employed or invented to increase the Peer-to-Peer (P2P) security like encryption, sandboxing, digital rights management, reputation, and firewall. Among those technologies, trust-reputation controlling mechanism, as an active self-controlling method is especially useful to automatically record, analyze and even adjust peers reputation trust credibility among the different peers so that the system can adjust itself according to the credibility changes. This kind of self-adjusting system is suitable for our anonymous, dynamic and variable P2P environment. Using the Resource Chain Model (RCM), the new P2P reputation-based trust model, we can find the best resource location both effectively and efficiently while maintaining the system security. The goal of this paper is to find whether the model can increase the successful download rate when the number of transactions and the number of malicious nodes are increasing. The study’s results show that RCM improved the performance. Thus, this approach enables one to find a better solution to find the best resource chain in a P2P community.